The Evaluation of Corn and Peanut Intercropping on Efficiency of Use the Environmental Resource and Soil Fertility
Bibliographic record
Abstract
Order to study the effect of density, the control weed and various proportion corn (704 Variety) and peanut (Goli Variety) intercropping an experiment was conducted in 2012 in Research station of agriculture, University of Zabol. The experiment design was factorial in randomized complete block design with three replications. Experiment factors consisted of planting proportions in 4 levels (sole crop of corn, 50% corn + 50% peanut, 100% corn + 100% peanut and sole crop of peanut), control weed in 3 levels (non-weeding, once-weeding and twice-weeding) and the space between rows in 2 level (40 and 50 cm) has been considered. The evaluated Characteristics in environmental sources are (Photosynthetic Active Radiation, Temperature and soil Moisture), the nutrients of soil include (N, K, Na, Mg, Ca, and C) and to evaluate intercropping of pure was used land equivalent ratio and economical yield. All Characteristics of study were affected by planting system.There was significant interaction between planting system, weeding and density in the absorption of light, temperature and moisture of soil. The results showed that photosynthesis active radiation absorbed by the intercropping was higher than sole crop in both plants. The results showed that changes in soil nutrient capacity of single elements (Na and K) in the treatment of mixed and monoculture peanut was more than monoculture corn and divalent elements (Ca and Mg) in mixed and monoculture corn more than mixed replacement and peanut monoculture. The highest land equivalent ratio (1.048) was accounted additive intercropping. Generally the mixed cultures with increasing density and control weed caused increase soil fertility and amount of soil nutrients after harvest. Treatment 100% Corn +100% peanut was the best treatment because using sources and increasing soil fertility and crop yield in comparison to sole crop.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".